Ontological scenario model for learners with disabilities in a recommender framework based on assessment analytics

Abstract

Technology Enhanced Learning Environments (TELE) have attracted many learners to acquire knowledge and skills at their own pace. But the majority of these environments are not accessible for all categories of learners including learners with disabilities. In fact, some environments may provide content during the learning process that does not meet the profiles of every type of disability. Much research has been developed in the area of personalizing e-learning for people with disabilities. The use of assessment analytics, on the other hand, remains largely unexploited despite its great informative potential, which is elated to assessment data generated by online learning environment. Our proposal focuses on the design of a scenario model for Assessment Analytics to develop a recommendation framework for learners with disabilities. This framework is conceived to retrieve and select relevant learning and assessment resources to learners with disabilities based on their preferences, accessibility needs, and assessment trace data in the context of online learning.